ABSTRACT A significant consequence of aging is reduced compliance (stiffening) of the large elastic arteries, which compromises their energy storage and pulse dampening function and increases the risk of adverse cardiovascular events. During development and maturation, production and deposition of the extracellular matrix (ECM) proteins, elastin and collagen, are regulated so that the aorta maintains appropriate mechanical properties defined by a physiological elastic modulus. Increased elastic modulus and consequently reduced arterial compliance with aging suggests that production of elastin and collagen becomes unsynchronized, resulting in collagen accumulation far exceeding that of elastin. This scar-like ECM results in elevated blood pressure as the heart pumps against a less compliant tube, increased arterial wall stress, and more collagen deposition in a negative feedback cycle. In this revision application we are requesting funds to expand the studies in our parent R01 on the control of ECM production during aortic development to include aging. We wish to specifically explore the mechanism behind the uncoupling of elastin and collagen accumulation and organization and whether TGF? signaling changes during aging. To accomplish our aims, we will use novel mouse models in which elastin amounts and, hence, aortic compliance, can be modulated. These models will be compared to the normal aging process in wild-type mice so that we can identify mechanisms behind the aortic pathology that occurs with aging when the appropriate physiological elastic modulus cannot be achieved. We will also continue to develop mathematical models incorporating hemodynamic forces, aortic wall structure and mechanical behavior, to better understand and predict the remodeling process in aging. Our specific aims are to: 1) Identify pathways that differentially regulate ECM production and smooth muscle cell proliferation in adaptive, normal, and pathological aortic aging; 2) Quantify how elastin and collagen amounts and organization remodel to affect the aortic modulus in aging; and 3) Integrate mechanical and physiological data into a mathematical model to better understand and predict aortic remodeling in aging.